Designing Data for Women with Rachel Elsinga
What is Equilo, and what led you to start it?
Equilo is a gender equality analysis platform that provides instant access to country and sector-specific data analysis, research, and recommendations. It provides decision makers with the information they need to be able to make better decisions to not only improve gender equality, but also improve investment and project outcomes. The key there is that improving gender equality is not just about improving the lives of women and girls, but it actually improves communities across the board. Gender equality touches everything.
I had been working in banking for ten years, and had a masters in international development. A friend of mine from the same Masters program became a gender specialist and she was doing this type of work manually as a consultant. She kept saying we need to get this information into more people’s hands and more efficiently—that there are only so many gender specialists and so demand is much greater. I was also ready to do more impactful work, and so we got together to create Equilo.
How does Equilo work?
We’re trying to make it really easy for people to connect the dots between gender equality issues specific to a particular country or sector. We spell out the “so what?” and “what should I do about it?”
Often people say that the hard part with gender equality is that there isn’t enough data. Yes, there is a problem with missing data – but also, there’s a lot of data out there siloed in different organisations. So we have pulled in data from the World Bank, the UN, country level survey data, etc (thousands of sources) and brought it all into one place to make it digestible.
We do that by boiling it down to a gender equality score across six different domains and 15 themes in 132 different countries. The idea of the score is to have a way to benchmark a country against its region, income group, etc — and there’s always room to dig deeper — but we are trying to simplify into a snapshot, so that people can at least digest the initial context to understand what is the gender equality situation in this country when it comes to power & decision making, laws & policies, culture & beliefs, human dignity, access to resources, and roles & responsibilities. As you dig in, you have access to the thousands of indicators that feed into each gender equality score, but at least the decision makers have a starting point with the scores highlighting what needs the most attention.
We started with analysis at country level, and are now rolling out sector content. We now have agriculture, energy, and infrastructure available. Finance and WASH are coming next month, with another 13 sectors by year-end. Also, so far Equilo data is for low- and middle-income countries. We do not have data on the middle-high and high income countries. But we’re actually finding that there’s a real demand for that as well.
What’s ironic is that gender equality reporting standards are often higher for developing countries – for example USAID will require all kinds of information before they do an infrastructure project in a developing country. And much of that same data is unavailable for the developed countries because they don’t have the same requirements. Usually it’s assumed that the private sector of developed countries are leading the way, but it’s actually the other way around here – we can learn from the rigor that is applied by government-funded projects in developing countries and put it into the private sector of developed countries.
What have you learned about designing for women as you’ve built Equilo?
When we design for women, we are designing for communities
There was a time that maternity leave policy in HR used to be discussed among women’s groups, and now that’s evolved to become parental leave and now men are also benefiting, and the children are benefiting. So when we Design for Women, we are actually designing for communities and the whole. Women are more likely to take a step back and bring everyone along instead of just focusing on themselves.
We need a gender-lens all the time to truly create impact
Things that seem like they have nothing to do with gender – such as snow plowing – are connected to gender. The status quo doesn’t understand that an energy project or an infrastructure project is related to gender. The first hurdle in designing for women is getting buy-in from men to not see the work as a charity project for gender equality but rather a smart business decision or risk mitigation.
For example, there was a time that corporations thought that they had nothing to do with ESG (Environmental, Social, and Corporate Governance), and now it’s totally standard to include it in their strategy and plans. That’s where we need to go with “GESI” (gender equality and social inclusion). Women and other minority groups think about things in a way the status quo just doesn’t — and this kind of thinking needs to come to the forefront.
How might we begin to advocate for a gender-lens across projects?
Understand the impact you can have
Let’s take WASH as an example. We recently helped Aqua for All understand the impact they can have if they save 15 minutes of a woman’s time by making access to clean water and sanitation easier. Most organisations would look at that in a very linear fashion – saving 15 minutes of a woman’s time means she can work for 15 more minutes. But the impact is much larger and has to do with much more than just her potential wage-earning activities. She might be able to rest more, or she might be able to boil water for longer which would reduce the incidence of stomach bugs in her family, it could reduce gender-based violence because she can come home earlier from work. It’s about connecting the dots and showing that a WASH project isn’t just about water accessibility, when designed with a gender lens — it’s also about all of these other factors that improve life for the community.
Make GESI (Gender Equality & Social Inclusion) part of standard evaluation criteria
We strive to connect the dots and show the impact so projects begin to take gender into consideration as a key factor for successful outcomes and/or risk mitigation. If an infrastructure project just spent millions of dollars building a new highway, but didn’t think about a wide enough and well-lit sidewalk for the women to walk on, then you are increasing the risk of gender based violence. They would then have to go back and spend more money to fix it. It’s just good business practice to make GESI part of the standard evaluation criteria.
Most development organizations require a GESI element, but still many project leads don’t understand gender linkages and therefore don’t adopt the recommendations. Many times, they will just include direct, surface data such as the number of women working in a particular sector. But this isn’t just about counting heads, it’s about seeing gender equality as a whole and how it impacts both the project-specific results as well as the community. And that applies well beyond the development sector and should be incorporated into the private sector as well.
Show the impact by example
When I worked in Finance, I worked in Risk Management. The hard part about risk is that you are successful when “X incident” didn’t happen. You are trying to help avoid a cost and you are trying to convince someone of the value of X never happening—and that your recommendations helped avoid X from happening. My prior experience has come in so handy with my work in gender, because often it’s about explaining the risks (such as gender based violence and the negative impacts this can have beyond the individual or family but on productivity and GDP) and why it’s in their favour to try and avoid these costs.
The best way to explain is via example. Microfinance programs are often available to women only due to their creditworthiness. This was a great opportunity for women entrepreneurs. However, in some cultures, where there was an increase in microlending to women, there was also an uptick in domestic violence. This was due to interfering with the power dynamic within the home. A gender analysis would highlight this as a risk and suggest a mitigation. In this case, it’s not to stop women-only microlending, but simply to include men in the training for Microfinance. Even without giving men access to loans, including them in the training helps them see the community benefit and be a part of it.
Another example from years back is when the Australian Air Force designed a rigorous training program for their pilots. A number of women passed the training, but when the women were brought to the newly rolled out jets, 27% of them couldn’t reach the brakes. These are all costs that could have been avoided if only a gender lens was taken to design the products and services.
What advice do you have for someone designing data for women?
Stories lives in the nuances of data—
Often we miss the stories data can tell us by not collecting or analyzing the right cut of data. For example, often data is collected at the household level, which means it is not sex segregated. We might know how many cars a household has, but we don’t know if women have access to those cars or if they own those cars. In developed countries too, we often take a myopic view looking at gender OR race, which means we only ever see a fraction of the story. We need to look at intersectional data that cuts across gender, race, income groups, sexual identity, etc to really pinpoint the root of the problem.
Understand what you are trying to measure & make sure you’re measuring it—
You can’t look at numbers in a vacuum. Figure out what your overall objective is and make sure your data solution is solving for the right piece. For example, a ton of corporations that have DEI programs often measure the wrong thing. In an effort to promote women, they will send the women for this and that training, while the men sit back and do their jobs. Male managers get pats on their backs for hosting women’s training – but are the trainings actually resulting in promotions? How will you measure that? Understand the reason behind your program, make sure everyone is on board with the reason and measure for that – instead of the surface measures like ‘X women attended this training.’
About Rachel Elsinga
Rachel is co-founder of Equilo, a gender equality data analysis and due diligence platform. It is a combined expression of her fierce feminist, inner data geek, and humanitarian sides. She also runs a small business, REE Works, offering start-up consulting services, financial forecasting, and portfolio analysis as well as being an active social impact investor. Previously, she spent 12 years in corporate banking based in New York, London, and Amsterdam with experience in relationship management and corporate advisory services for multinational clients and credit risk management covering Africa, Middle East, and Central Europe. She has social impact investing and advising experience in housing solutions for displaced populations, fintech, and ecotourism. Rachel received a MBA and MPP in International Development from Georgetown University and a BA in Economics from the University of Michigan.